Users in various fields, for instance, users in the public or private sectors rely on a varied set of documents for daily functions. A single document such as a driver's license, a passport, a bill of lading form, or a shipping receipt may include various kinds of information. For example, a passport information page may include a photo section; a text section with a name and features, such as height, weight, and hair color; a graphics section with the driver's signature; one or more bar codes; and a machine readable zone. Information may be obtained from these documents with a scanning device which may be configured to read radio frequency identifier (RFID) tags and barcodes and/or retrieve an image of a document.
Subsequent to capturing information from the document, the format of certain types of information, for example, the format of barcodes, enable them to be easily and quickly identified and decoded. An Optical Character Recognition (OCR) engine may be used to convert a scanned image of the document into alphanumeric characters that can be further analyzed. However, the quality of the scanned image may affect the decoding rate associated with decoding the alphanumeric characters in the scanned image. For instance, a complex background on a scanned image of a passport information page may make it difficult for the OCR engine to decode text in, for example, a Machine Readable Zone (MRZ) on the passport information page. Therefore, the scanning device may not be about to decode text in one section of the document as efficiently as it could decode a barcode in another section of the same document.
A current scanning device uses multiple OCR engines to decode information retrieved from one input image. Each OCR engine in the scanning device outputs decoded information where the accuracy of the texts in each output is determined by corresponding confidence values. In order to select the output with the most accurate text, the outputs from the OCR engines in the scanning device are prioritized. Another scanning device uses multiple binarization methods, each of which produces a binary image that is generated from a single input image. The binary images are used to generate OCR results, where each OCR result is associated with a set of corresponding confidence values that are used to select the most accurate OCR result. The quality of the image inputted into the scanning device with multiple OCR engines and the scanning device using multiple binarization methods may affect the decoding rate and process such that each of these scanning devices may not be able to decode information in one section of the input image, for example, alphanumeric characters in one section of the input image, as efficiently as it could decode information, such as barcodes, in other sections of the input image.
Accordingly, there is a need for an improved method and apparatus for scanning and decoding information in an identified location in the document.
Skilled artisans will appreciate that elements in the figures are illustrated for simplicity and clarity and have not necessarily been drawn to scale. For example, the dimensions of some of the elements in the figures may be exaggerated relative to other elements to help to improve understanding of embodiments of the present invention.
The apparatus and method components have been represented where appropriate by conventional symbols in the drawings, showing only those specific details that are pertinent to understanding the embodiments of the present invention so as not to obscure the disclosure with details that will be readily apparent to those of ordinary skill in the art having the benefit of the description herein.